In vivo Mouse Model of Spinal Implant Infection.

Spine implant infections portend poor outcomes as diagnosis is challenging and surgical eradication is at odds with mechanical spinal stability. The purpose of this method is to describe a novel mouse model of spinal implant infection (SII) that was created to provide an inexpensive, rapid, and accurate in vivo tool to test potential therapeutics and treatment strategies for spinal implant infections. In this method, we present a model of posterior-approach spinal surgery in which a stainless-steel k-wire is transfixed into the L4 spinous process of 12-week old C57BL/6J wild-type mice and inoculated with 1 x 103 CFU of a bioluminescent strain of Staphylococcus aureus Xen36 bacteria. Mice are then longitudinally imaged for bioluminescence in vivo on post-operative days 0, 1, 3, 5, 7, 10, 14, 18, 21, 25, 28, and 35. Bioluminescence imaging (BLI) signals from a standardized field of view are quantified to measure in vivo bacterial burden. To quantify bacteria adhering to implants and peri-implant tissue, mice are euthanized and the implant and surrounding soft tissue are harvested. Bacteria are detached from the implant by sonication, cultured overnight and then colony forming units (CFUs) are counted. The results acquired from this method include longitudinal bacterial counts as measured by in vivo S. aureus bioluminescence (mean maximum flux) and CFU counts following euthanasia. While prior animal models of instrumented spine infection have involved invasive, ex vivo tissue analysis, the mouse model of SII presented in this paper leverages noninvasive, real time in vivo optical imaging of bioluminescent bacteria to replace static tissue study. Applications of the model are broad and may include utilizing alternative bioluminescent bacterial strains, incorporating other types of genetically engineered mice to contemporaneously study host immune response, and evaluating current or investigating new diagnostic and therapeutic modalities such as antibiotics or implant coatings.

A systematic overview of systematic reviews evaluating interventions addressing polypharmacy.

PURPOSE: To systematically evaluate and summarize evidence across multiple systematic reviews (SRs) examining interventions addressing polypharmacy. SUMMARY: MEDLINE, the Cochrane Database of Systematic Reviews, and the Database of Abstracts of Reviews of Effects (DARE) were searched for SRs evaluating interventions addressing polypharmacy in adults published from January 2004 to February 2017. Two authors independently screened, appraised, and extracted information. SRs with Assessment of Multiple Systematic Reviews (AMSTAR) scores below 8 were excluded. After extraction of relevant conclusions from each SR, evidence was summarized and conclusions compared. Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to assess evidence quality. Six SRs met the inclusion criteria, 4 of which used meta-analytic pooling. Five SRs focused on older adults. Four were not restricted to any specific disease type, whereas 1 focused on proton pump inhibitors and another focused on patients with severe dementia. Care settings and measured outcomes varied widely. SRs examining the impact on patient-centered outcomes, including morbidity, mortality, patient satisfaction, and utilization, found inconsistent evidence regarding the benefit of polypharmacy interventions, but most concluded that interventions had either null or uncertain impact. Two SRs assessing medication appropriateness found very low-quality evidence of modest improvements with polypharmacy interventions. CONCLUSION: An overview of SRs of interventions to address polypharmacy found 6 recent and high-quality SRs, mostly focused on older adults, in which both process and outcome measures were used to evaluate interventions. Despite the low quality of evidence in the underlying primary studies, both SRs that assessed medication appropriateness found evidence that polypharmacy interventions improved it. However, there was no consistent evidence of any impact on downstream patient-centered outcomes such as healthcare utilization, morbidity, or mortality.